68 citations · 222 across the 14 of their papers we have counts for
16 papers
Learning beyond sensations: how dreams organize neuronal representations
Nicolas Deperrois, Mihai A. Petrovici, Walter Senn +1
Semantic representations in higher sensory cortices form the basis for robust, yet flexible behavior. These representations are acquired over the course of development in an unsupe…
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons
Paul Haider, Benjamin Ellenberger, Laura Kriener +3
The response time of physical computational elements is finite, and neurons are no exception. In hierarchical models of cortical networks each layer thus introduces a response lag.…
Learning cortical representations through perturbed and adversarial dreaming
Nicolas Deperrois, Mihai A. Petrovici, Walter Senn +1
Humans and other animals learn to extract general concepts from sensory experience without extensive teaching. This ability is thought to be facilitated by offline states like slee…
Conductance-based dendrites perform Bayes-optimal cue integration
Jakob Jordan, João Sacramento, Willem A. M. Wybo +2
A fundamental function of cortical circuits is the integration of information from different sources to form a reliable basis for behavior. While animals behave as if they optimall…
Evolving Neuronal Plasticity Rules using Cartesian Genetic Programming
Henrik D. Mettler, Maximilian Schmidt, Walter Senn +2
We formulate the search for phenomenological models of synaptic plasticity as an optimization problem. We employ Cartesian genetic programming to evolve biologically plausible huma…
Natural-gradient learning for spiking neurons
Elena Kreutzer, Walter M. Senn, Mihai A. Petrovici
In many normative theories of synaptic plasticity, weight updates implicitly depend on the chosen parametrization of the weights. This problem relates, for example, to neuronal mor…